Ignaty Leshchiner, Edmund A Mroz, Justin Cha, Daniel Rosebrock, Oliver Spiro, Juliana Bonilla-Velez, William C Faquin, Armida Lefranc-Torres, Derrick T Lin, William A Michaud, Gad Getz, James W Rocco <<<

Analysis of premalignant tissue has identified the typical order of somatic events leading to invasive tumors in several cancer types. For other cancers, premalignant tissue is unobtainable, leaving genetic progression unknown. Here, we demonstrate how to infer progression from exome sequencing of primary tumors. Our computational method, PhylogicNDT, recapitulated the previous experimentally determined genetic progression of human papillomavirus-negative (HPV) head and neck squamous cell carcinoma (HNSCC). We then evaluated HPV HNSCC, which lacks premalignant tissue, and uncovered its previously unknown progression, identifying early drivers. We converted relative timing estimates of driver mutations and HPV integration to years before diagnosis based on a clock-like mutational signature. We associated the timing of transitions to aneuploidy with increased intratumor genetic heterogeneity and shorter overall survival. Our approach can establish previously unknown early genetic progression of cancers with unobtainable premalignant tissue, supporting development of experimental models and methods for early detection, interception and prognostication. <<<

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data. <<<

Neoantigen vaccines aiming to induce tumor-specific T cell responses have achieved promising antitumor effects in early clinical trials. However, the underlying mechanism regarding response or resistance to this treatment is unclear. Here we observe that neoantigen vaccine-generated T cells can synergize with the immune checkpoint blockade for effective tumor control. Specifically, we performed single-cell sequencing on over 100,000 T cells and uncovered that combined therapy induces an antigen-specific CD8 T cell population with active chemokine signaling (Cxcr3/Ccl5), lower co-inhibitory receptor expression (Lag3/Havcr2) and higher cytotoxicity (Fasl/Gzma). Furthermore, generation of neoantigen-specific T cells in the draining lymph node is required for combination treatment. Signature genes of this unique population are associated with T cell clonal frequency and better survival in humans. Our study profiles the dynamics of tumor-infiltrating T cells during neoantigen vaccine and immune checkpoint blockade treatments and high-dimensionally identifies neoantigen-reactive T cell signatures for future development of therapeutic strategies. <<<

David Tamborero, Rodrigo Dienstmann, Maan Haj Rachid, Jorrit Boekel, Adria Lopez-Fernandez, Markus Jonsson, Ali Razzak, Irene Braña, Luigi De Petris, Jeffrey Yachnin, Richard D Baird, Yohann Loriot, Christophe Massard, Patricia Martin-Romano, Frans Opdam, Richard F Schlenk, Claudio Vernieri, Michele Masucci, Xenia Villalobos, Elena Chavarria, Cancer Core Europe consortium, Judith Balmaña, Giovanni Apolone, Carlos Caldas, Jonas Bergh, Ingemar Ernberg, Stefan Fröhling, Elena Garralda, Claes Karlsson, Josep Tabernero, Emile Voest, Jordi Rodon, Janne Lehtiö <<<

There is a growing need for systems that efficiently support the work of medical teams at the precision-oncology point of care. Here, we present the implementation of the Molecular Tumor Board Portal (MTBP), an academic clinical decision support system developed under the umbrella of Cancer Core Europe that creates a unified legal, scientific and technological platform to share and harness next-generation sequencing data. Automating the interpretation and reporting of sequencing results decrease the need for time-consuming manual procedures that are prone to errors. The adoption of an expert-agreed process to systematically link tumor molecular profiles with clinical actions promotes consistent decision-making and structured data capture across the connected centers. The use of information-rich patient reports with interactive content facilitates collaborative discussion of complex cases during virtual molecular tumor board meetings. Overall, streamlined digital systems like the MTBP are crucial to better address the challenges brought by precision oncology and accelerate the use of emerging biomarkers. <<<